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Improving environmental sensor data quality using a categorization of data properties.

, , and . ICIQ, MIT Information Quality Program, (2010)

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Multi-objective optimization under positivity constraints, with a meteorological example., , , , and . FUZZ-IEEE, page 1-7. IEEE, (2010)Semi-Automated Semantic Segmentation of Arctic Shorelines Using Very High-Resolution Airborne Imagery, Spectral Indices and Weakly Supervised Machine Learning Approaches., , , , , and . Remote. Sens., 13 (22): 4572 (2021)Improving environmental sensor data quality using a categorization of data properties., , and . ICIQ, MIT Information Quality Program, (2010)DaProS: A Data Property Specification Tool to Capture Scientific Sensor Data Properties., , and . ER Workshops, volume 6413 of Lecture Notes in Computer Science, page 232-241. Springer, (2010)How to Predict Nesting Sites and How to Measure Shoreline Erosion: Fuzzy and Probabilistic Techniques for Environment-Related Spatial Data Processing., , , and . WCSC, volume 361 of Studies in Fuzziness and Soft Computing, page 595-604. Springer, (2016)Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem., , , , and . Remote Sensing, 9 (10): 1071 (2017)Image inpainting in micrometeorological analysis., , , and . ICIP, page 1725-1728. IEEE, (2012)Can Plot-Level Photographs Accurately Estimate Tundra Vegetation Cover in Northern Alaska?, , , , , , , and . Remote. Sens., 15 (8): 1972 (April 2023)Arctic Tundra Vegetation Functional Types Based on Photosynthetic Physiology and Optical Properties., , , , , and . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 6 (2-1): 265-275 (2013)Towards an International Polar Data Coordination Network., , , , , , , , , and 4 other author(s). Data Sci. J., (2014)